Projects

Ongoing

Encouraged by the results of the earlier ewz-Amphiro-study, this randomized controlled trial evaluates the effects of and mechanisms behind different feedback interventions that target water and energy consumption. This project is in collaboration with Mobiliar Insurance.

The key objective of this project is to develop further and evaluate feature extraction and machine learning techniques for automatic identification of household properties based on electricity load profiles.

Together with colleagues at the National University of Singapore (Department of Real Estate) and Singapore’s Public Utilities Board , we have developed and are conducting a field experiment to assess the effectiveness of technology-based water conservation strategies in a field trial in Singapore.

The DAIAD project constitutes an innovative approach for addressing the challenge of efficient water management through real-time knowledge of residential water consumption, bringing together leading members of the water and ICT domain.

In this completed project, we provided real-time feedback to individuals on their energy and water use in the shower. We had been able to win the utility company ewz as corporate partner in this project and our research activities in this project were funded by a grant by the Swiss Federal Office of Energy.

We investigate commercially attractive compromise between the computational power needed and recognition accuracy achieved for disaggregating consumption data in order to identify individual devices or groups of devices.